To electronically enlarge an image, linear interpolation, such as the one employing a bilinear method, or a bicubic method has been used. With such linear interpolation, a sense of high resolution or sharpness of the image tends to be lowered as the enlargement factor increases. As a method for obtaining a high-resolution image with a high sense of sharpness, a super-resolution process using a learned database is known. This method refers to a database in which examples of correspondence relations between high-resolution images and low-resolution images have been accumulated, to predict high-resolution components which are not present in the input image, thereby to achieve conversion to a higher resolution.
For example, in the super-resolution process described in patent reference 1, a search vector is generated for each of the patches formed by dividing an interpolated image, and a high-frequency component data corresponding to an index vector having the highest similarity to the search vector is read from a learned database to generate a patch of a high resolution.